Abstract

Background and significance: B-cell acute lymphoblastic leukemia (B-ALL) is characterized by dynamic shifts between activation and quiescence. These cycles are predicated by fluctuations in oncogenic signaling, which mimic pre-BCR and cytokine receptor signaling, e.g. IL7 receptor signaling and phosphorylation of STAT5. These fluctuations in cytokine receptor and STAT5 signaling are mitigated by powerful feedback regulators, including CISH and SOCS (suppressors of cytokine signaling) family members. While B-ALL cells depend on oncogenic STAT5 signaling, CISH and SOCS2 negative feedback regulators of STAT5 are highly expressed in aggressive B-ALL and high expression levels are strongly linked to poor clinical outcome, positive MRD and increased likelihood of bone marrow relapse in children (COG P9906) and adults (ECOG E2993). To determine whether high levels of CISH and SOCS2 are biomarkers of high oncogenic STAT5 signaling or mechanistically contribute to clonal fitness and adaptability of B-ALL, we performed genetic experiments in mouse models for B-ALL. Here we examined the mechanisms and consequences of active and inactive states of STAT5 by studying constitutively active (CA) and non-phosphorylatable Y694F (YF) mutations of STAT5. Results: Consistent with a central role of STAT5-feedback control in B-ALL survival, inducible ablation of Cishfl/fl resulted in rapid depletion of B-ALL cells. Socs2-/- B-ALL cells rapidly underwent cellular senescence, lacked colony forming and leukemia-initiating capacity in serial transplantation experiments. Likewise direct interference with STAT5-function, by mutations resulting in constitutive activation (STAT5-CA) or an inactive state (STAT5-YF). Consistent with a requirement of adaptive STAT5-feedback control in B-ALL, both Stat5-CA and Stat5-YF resulted in rapid cell death. Induction of Stat5-CA caused accumulation of biomass indicated by their increased cell size, whereas Stat5-YF caused rapid cell shrinkage ( Figure A). To determine whether the mTOR cell growth pathway was responsible for cell death induced by Stat5-CA, we tested whether the genetic deletion of Mtor or pharmacological inhibition of protein synthesis were sufficient to rescue B-ALL cell death. As expected, B-ALL cells retaining intact Mtor rapidly underwent energy crisis and cell death, while genetic deletion of Mtor reversed the toxic effects of Stat5-CA, suggesting that Stat5-CA is associated with excessive protein synthesis and defective ER turnover. Indeed, Stat5-CA increased protein synthesis rate and ER content compared to EV control, and these effects were opposed by Stat5-YF. To compare the metabolic outcomes of Stat5-CA and Stat5-YF, we performed mass spectrometry-based metabolomic analyses ( Figure B). Consistent with the role of mTOR in promoting glycolysis, Stat5-CA increased the content of glycolytic intermediates in B-ALL cells. In contrast, Stat5-YF increased phospholipid intermediates and phosphatidylethanolamine (PtdEtn). Opposed by Myc, Stat5-YF increased the expression levels of Bcl6 and autophagic genes, suggesting that Bcl6-dependent programs promote PtdEtn-LC3B conjugation, thereby autophagosome formation. As expected, microscopic validation with LC3B-GFP reporter revealed that Stat5-YF increased the number of LC3B-GFP puncta, upon pharmacological inhibition of autophagosome-lysosome fusion ( Figure A). Consistent with STAT5-CA promoting Myc- as opposed to STAT5-YF driving Bcl6-dependent programs, a flow cytometry analysis of Myc-eGFP/Bcl6-mCherry dual reporter expression in murine B-ALL cells demonstrated that changes between glycolytic Myc+ and autophagic Bcl6+ states were the direct consequence of Stat5-CA and Stat5-YF induction, respectively. Conclusions: Our results demonstrate feedback regulators of STAT5, including SOCS2 and CISH are not only biomarkers of increased oncogenic STAT5 activity and a more aggressive course of disease linked to poor overall outcomes. Importantly, negative STAT5 feedback control mechanisms are essential to enable nimble adaptations of B-ALL cells in response to fluctuations of oncogenic signaling strength and availability of nutrients during distinct metabolic states of cellular activation (MYC) and quiescence (BCL6).

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